IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v12y2016i6p1289013.html
   My bibliography  Save this article

BigLoc: A Two-Stage Positioning Method for Large Indoor Space

Author

Listed:
  • Zengwei Zheng
  • Yuanyi Chen
  • Sinong Chen
  • Lin Sun
  • Dan Chen

Abstract

With the rapid development of WLAN infrastructure, fingerprint-based positioning using signal strength has become a promising localization solution in indoor space. Commonly fingerprint-based positioning methods face two challenges in large indoor space, one is floor recognition in large building with multifloor, and the other is signal strength variance due to heterogeneous devices and environmental factors. In this paper, we propose a novel two-stage positioning approach to address these challenges of fingerprint-based positioning methods in large indoor space. Firstly, we design a floor-level recognition feature based on WiFi access points and the RSS values to recognize floor. For solving the signal strength variance problem, we propose a new metric to capture the similarity of location fingerprints probability distribution using KL Divergence. To demonstrate the utility of our approach, we have performed comprehensive experiments in a large indoor building.

Suggested Citation

  • Zengwei Zheng & Yuanyi Chen & Sinong Chen & Lin Sun & Dan Chen, 2016. "BigLoc: A Two-Stage Positioning Method for Large Indoor Space," International Journal of Distributed Sensor Networks, , vol. 12(6), pages 1289013-128, June.
    • Handle: RePEc:sae:intdis:v:12:y:2016:i:6:p:1289013
    DOI: 10.1155/2016/1289013
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1155/2016/1289013
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2016/1289013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:12:y:2016:i:6:p:1289013. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.